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5th International Conference on information Management and Machine Intelligence, ICIMMI 2023

作者： Mundada, Shyamal Jain, Pooa Department of Computer Science and Engineering Indian Institute of Information Technology Nagpur India

ISBN: (纸本)9798400709418

Agriculture is one of the most important industries for the country in terms of sustainability and the economy. Agriculture practises must be improved to preserve a sustainable balance because agriculture's importance and requirement are increasing along with the population. A vital part of the agricultural system is the soil. The accurate and thorough spatial soil information provided by soil composition detection can assist farmers in making decisions that will promote the growth of their crops. As a result, researchers concentrated on using AI and remote sensing to create models for the prediction of soil nutrient information that will aid farmers in exact fertilisation. A precise and economical solution for soil nutrient mapping is now available due to recent developments in sensor technology and machine learning-based soil analysis methods. Therefore, using machine learning (ML) techniques on remote sensing data can aid in developing a precision farming decision support system to increase crop output. For environmental modelling and risk assessment, complete and accurate geographic soil information is crucial. © 2023 ACM.

关键词： Soils

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Development of Deepfake Detection Techniques for Protecting Multimedia information using Deep Learning 3

Development of Deepfake Detection Techniques for Protecting ...

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3rd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2024

作者： Siva Rama Lingham, N. Devakanth, J Jude Moses Anto Raj, Gowtham Gayathri, K. Janani, R. Dhanapal, R. Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Chennai India Acharya Institute of Technology Department of Computer Science and Engineering Bangalore India Bannari Amman Institute of Technolgy Department of Information Technology Erode India Sri Krishna College of Engineering and Technology Department of Computer Science and Engineering Coimbatore India Karpagam Academy of Higher Education Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350375190

The development of proposed deepfake detection techniques plays a prominent role in the safeguarding the multimedia information. The various challenges are addressed using the aid of deep learning techniques. This involves hybrid optimization techniques such as particle swarm optimization and genetic algorithms. This helps to improve the accuracy and efficiency in the detection of deepfake. PSO helps in optimizing the weights and parameters of the neural network to obtain faster convergence. GA helps in obtaining potential solutions to obtain the robust deepfake detection model. The integration of deep learning with hybrid optimization involves the collection and preprocessing of the multimedia information and proceeds to an optimization algorithm. The manipulated content in the online platform are detected during the training process. The hybrid optimization tcehniques helps in obtaining model generability and achieving resilience in various attacks occurring in the deepfake generation. The integration of PSO and GA helps in the accurate detection of deepfake content through continuous training and evaluation. Thus the proposed system forms a safeguarding tool for multimedia content and helps to eliminate various risks. © 2024 IEEE.

关键词： Genetic algorithms

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Design and Implementation of "Fighting and Dream" E-Sports Data Management system 3

Design and Implementation of "Fighting and Dream" E-Sports D...

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3rd International Conference on Artificial Intelligence, Big Data and Algorithms, CAIBDA 2023

作者： Mao, Tingting Lu, Junwei Department of Computer Science and Technology Dalian Neusoft University of Information Dalian China

ISBN: (纸本)9781643684444

With the rapid development of modern information technology, an industry named 'E-sports' was born. The significance of this project lies in providing convenience for E-sports management through the Spring Boot, *** and Mybatis development system. In this system, players can query event data or training arrangements, complete their training tasks in a timely manner, or provide feedback to coaches. Players need to check the official competition arrangements through the system to participate in the competition. Coaches can query the competition data and schedule of players, arrange training arrangements for each player in their team, or provide feedback to the organizers. The organizer can not only arrange the competition and publish it in the system, but also make modifications to various details such as the competition. © 2023 The Authors.

关键词： information management

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Intelligent Aquila Optimization Algorithm-Based Node Localization Scheme for Wireless Sensor Networks

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computers, Materials & Continua 2023年第1期74卷 141-152页

作者： Nidhi Agarwal M.Gokilavani S.Nagarajan S.Saranya Hadeel Alsolai Sami Dhahbi Amira Sayed Abdelaziz Department of Information Technology KIET Group of InstitutionsDelhi201206India Department of Computer Science and Engineering Indira Gandhi Delhi Technical University for WomenNew DelhiDelhi110006India Department of Computer Science and Engineering KL UniversityVaddeswaramAndhra Pradesh522502India Department of Electronics&Communication Engineering Saveetha Engineering CollegeChennai602105India Department of Computer Science and Engineering K.Ramakrishnan College of EngineeringTiruchirapalli621112India Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversityMuhayel Aseer62529Saudi Arabia Department of Digital Media Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt

In recent times,wireless sensor network(WSN)finds their suitability in several application areas,ranging from military to commercial *** nodes in WSN are placed arbitrarily in the target field,node localization(NL)becomes essential where the positioning of the nodes can be determined by the aid of anchor *** goal of any NL scheme is to improve the localization accuracy and reduce the localization error *** this motivation,this study focuses on the design of Intelligent Aquila Optimization Algorithm Based Node Localization Scheme(IAOAB-NLS)for *** presented IAOAB-NLS model makes use of anchor nodes to determine proper positioning of the *** addition,the IAOAB-NLS model is stimulated by the behaviour of *** IAOAB-NLS model has the ability to accomplish proper coordinate points of the nodes in the *** guaranteeing the proficient NL process of the IAOAB-NLS model,widespread experimentation takes place to assure the betterment of the IAOAB-NLS *** resultant values reported the effectual outcome of the IAOAB-NLS model irrespective of changing parameters in the network.

关键词： Aquila optimizer node localization WSN intelligent models unknown nodes anchor nodes

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How Can CoPs in Scaled Agile Settings Look Like? Toward a Taxonomy for CoPs in Large-Scale Agile Software Development 58

How Can CoPs in Scaled Agile Settings Look Like? Toward a Ta...

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58th Hawaii International Conference on system sciences, HICSS 2025

作者： Tobisch, Franziska Schmidt, Johannes Matthes, Florian Technical University of Munich School of Computation Information and Technology Department of Computer Science Garching Germany

ISBN: (纸本)9780998133188

Fast-changing business environments and customer needs require organizations to react quickly and adapt to changes. While agile software development methods can support organizations in achieving this goal, applying these methods in a large context, like multi-team projects, entails high complexity. Several scaling agile frameworks recommend Communities of Practice (CoP), groups of people with a shared interest that exchange with each other on a regular basis, to support the application of agile at scale, as they can foster, e.g., inter-team collaboration and alignment. Still, no clear overview of aspects that must be considered when establishing and cultivating CoPs in scaled agile settings exists. Therefore, we propose a taxonomy for CoPs in this context, building on literature and findings of an interview study. The taxonomy can support practitioners and researchers, offering a structured overview of aspects relevant to establishing and cultivating CoPs in large-scale agile settings and future research directions. © 2025 IEEE computer Society. All rights reserved.

关键词： Software design

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Industrial IoT systems for Real-Time Environmental Monitoring

Industrial IoT Systems for Real-Time Environmental Monitorin...

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2024 International Conference on Advances in Computing Research on science Engineering and technology, ACROSET 2024

作者： Seth, Jyoti Dutta, Abhishek Desai, Karishma Vivekananda Global University Department of Computer Science & Engineering Jaipur India Department of Computer Science and Information Technology Bangalore India Atlas SkillTech University Department of UGDX Mumbai India

ISBN: (纸本)9798350388800

Innovative technology adoption is crucial for sustainable industrial practices in today's dynamic business climate. EcoSense360 is a revolutionary Industrial Internet of Things (IIoT) system for continuous environmental monitoring in manufacturing facilities, and it is presented in this article. Real-time anomaly detection, predictive maintenance, and energy optimization are the three cornerstone algorithms that make up EcoSense360. As the foundation of EcoSense360, the Real-Time Anomaly Detection Algorithm enables for instantaneous detection of environmental aberrations. The potential for environmental catastrophes is reduced, and crucial concerns may be addressed promptly, thanks to these real-time capabilities. Our testing shows that as compared to conventional approaches, EcoSense360 provides superior outcomes in terms of both data precision and real-time responsiveness, as well as regulatory compliance. EcoSense360 is a proactive and all-encompassing solution for environmental monitoring and management. Real-time environmental insights, predictive maintenance, and sustainable energy use are just a few of the ways in which its algorithms are changing the face of industry. Analysis shows EcoSense360 is superior to conventional approaches to environmental protection, resource conservation, and meeting sustainability targets. EcoSense360 is the best option for businesses that are serious about being environmentally responsible as they face increasing pressure to do so. © 2024 IEEE.

关键词： Environmental monitoring

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Enhanced Physical Layer Security for Full-Duplex Symbiotic Radio with AN Generation and Forward Noise Suppression

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IEEE Transactions on Communications 2024年第7期72卷 3905-3918页

作者： Jin, Chi Chang, Zheng Hu, Fengye Chen, Hsiao-Hwa Hamalainen, Timo University of Jyväskylä Faculty of Information Technology Jyväskylä40014 Finland University of Electronic Science and Technology of China School of Computer Science and Engineering Chengdu611731 China Jilin University College of Communication Engineering Changchun130012 China National Cheng Kung University Department of Engineering Science Tainan70101 Taiwan

Due to the constraints on power supply and limited encryption capability, data security based on physical layer security (PLS) techniques in backscatter communications has attracted a lot of attention. In this work, we propose to enhance PLS in a full-duplex symbiotic radio (FDSR) system with a proactive eavesdropper, which may overhear the information and interfere legitimate communications simultaneously by emitting attack signals. To deal with the eavesdroppers, we propose a security strategy based on pseudo-decoding and artificial noise (AN) injection to ensure the performance of legitimate communications through forward noise suppression. A novel AN signal generation scheme is proposed using a pseudo-decoding method, where AN signal is superimposed on data signal to safeguard the legitimate channel. The phase control in the forward noise suppression scheme and the power allocation between AN and data signals are optimized to maximize security throughput. The formulated problem can be solved via problem decomposition and alternate optimization algorithms. Simulation results demonstrate the superiority of the proposed scheme in terms of security throughput and attack mitigation performance. 0090-6778 © 2024 IEEE.

关键词： Backscattering

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Finding Robotic Wide Free Space Path in Dynamic Environment by Improving MAX–MIN Ant system Algorithm

International Journal of Interactive Mobile Technologies

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International Journal of Interactive Mobile Technologies 2023年第13期17卷 59-78页

作者： Hasan, Ali Hadi Abdullah, Hasanen S. Saleh, Mohamad Ab. College of Information Technology University of Babylon Babylon Iraq Department of Computer Science University of Technology Baghdad Iraq College of Economic and Administration Al Iraqia University Baghdad Iraq

This paper proposes a new obstacle avoidance method for finding an optimal path passing through wide free space based on the optimized MAXMIN Ant system (MMAS) algorithm in dynamic environments. The proposed improvement of the MMAS algorithm occurs in two stages. The first stage analyses the environment with two modifications by proposing a new relation of pheromone trail updating to construct the consequence modified (deposited) pheromone trail update in each iteration based on adding a new parameter (clean) to calculate the possible wide empty locations. Another alteration at this level involves checking and identifying the four horizontal and vertical states. Suppose the two nodes on either side of the four diagonal nodes are barriers in the next neighbor locations. In that case, the Tight Tunnel state is then attained, and it is managed by sealing this location to prevent passing through it before the robot movement stage. Another alteration is made to the robot-moving stage by recommending a new relation of tour building probabilities to determine the best option for moving the robot from the start node through a dynamic environment that incorporates dynamic obstacles moving through free space by locating and exhibiting the ideal path via broad free space. The main outcome of the experiment simulation of the new method involves that the robot avoids going through narrow tunnels and chooses the best course through open areas to reach its destination without running into any impediments in various dynamic environments conditions. In addition, the comparison of average time occupied to find the paths by the new method reduces to 54.32% as compared with that required with the method of hybrid the basic D* algorithm with the Lbest PSO algorithm, and to 11.95% in comparison to the time occupied recorded when applying the method of the improved MAX–MIN ACO algorithm. © 2023, International Journal of Interactive Mobile Technologies. All Rights Reserved.

关键词： Location

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Intelligent Street Light Management system using Solar Panels 3

Intelligent Street Light Management System using Solar Panel...

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3rd IEEE Delhi Section Flagship Conference, DELCON 2024

作者： Venkatraman, Akila Ruchitha, Arutla Sellamuthu, Suseela Shalini, Dappu Reddy, Pulsani Dinesh Gokaraju Rangaraju Institute of Engineering and Technology Department of Information Technology Hyderabad India Vellore Institute of Technology Department of Computer Science & Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798331518592

The conventional street lighting system is used during night time. It consumes more amount of power and there is major energy demand arises. The energy saving methods and lighting control arises to overcome the problem. The smart street light project aims to improve the energy efficiency and urban safety by using sensor- equipped street lights. It can adjust their brightness automatically based on levels of ambient light and the presence of vehicles and pedestrians. Additionally, the project incorporates the central management system implemented by using the ESP 32 module and BLYNK cloud, that allows for remote monitoring and control of street lights. The implementation of this technology can lead to significant cost saving, improves security for the cities and rise the overall quality of life for residents. Vehicle detection system is implemented to control the street lights when vehicle is detected. LED's (Light Emitting Diode) doesn't consume large amount of electricity. By the combination of both LED's and LDR's (Light Dependent Resistor) the intensity of light can be controlled and save more electricity. To make a step towards green energy, solar panels are used to power the street lights. The increased standard of living and growth of cities lead to the complex lighting system with automatic and intelligent control schemes. © 2024 IEEE.

关键词： Energy efficiency

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Optimized Hybrid CNN-GRU Approach for Accurate Prediction of Cardiovascular Diseases: Integrating Medical Imaging and Clinical Data 3

Optimized Hybrid CNN-GRU Approach for Accurate Prediction of...

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3rd International Conference on Communication, Control, and Intelligent systems, CCIS 2024

作者： Prasanna, V. Suresh Kumar, N. Divyaprabha, P. Sundaram, R. Srm Institute of Science and Technology School of Computing Faculty of Engineering and Technology Department of Data Science and Business Systems Chennai India Sri Ramakrishna Engineering College Department of Information Technology Coimbatore India Sri Ramakrishna Engineering College Department of Computer Science and Engineering Coimbatore India Ganesh College of Engineering Department of Computer Science and Engineering Salem India

ISBN: (纸本)9798331528201

As the primary cause of death globally, cardiovascular diseases (CVDs) demand precise and timely prediction to enhance patient outcomes. Other examples of conventional approaches for CVD prediction include statistical models as well as machine learning models such as a single model that often struggle to address complex and comprehensive data from clinical records and Medical Imaging. To address these issues, the concept proposed here is to integrate the medical imaging data with clinical data as new apart from utilizing the hybrid CNN-GRU model to predict cardiovascular diseases with higher accuracy and interpretability. While the GRU module deals with the time sequences of clinical data including past history and other test results, the CNN module is to extract the spatial features from the medical images. Thus, by integrating these modules, it is more accurate to predict the data of the patient as a synergy of spatial and temporal arrangements. Cross-validation techniques and performance indices are used for model training and testing on a diverse data set containing imaging and other clinical-related data. Experimental results depict that the suggested hybrid CNN-GRU model performs much better than the traditional approaches and has higher levels of predicted accuracy and robustness. It is also feasible to generalize this integrated strategy to other medical disorder where multi-modal data analysis is crucial, besides enhancing the capacity to estimate CVDs. The findings underline the importance of integrating doctors' information with radiological images and applying new patterns of neural networks to augmenting clinical judgment. The suggested work is implemented using python. © 2024 IEEE.

关键词： Recurrent neural networks

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